The Natural Resources Program Center conducted a land cover analysis to determine land cover types, acres and their subsequent percentages for the National Wildlife Refuge System. The National Land Cover Database (NLCD) 2001 was used to determine land cover classes and calculate number of acres at national and regional scales. Coordination Areas, National Wildlife Refuges, Wildlife Management Areas and Waterfowl Production Areas were extracted from the U.S. Fish and Wildlife Service interest boundary. Excluding Hawaii and Puerto Rico, other pacific and Caribbean were not included in the analysis due to absence of land cover data in the area. The FwsInterest feature class is an aggregated data layer derived by appending separate regional feature data sets into a single national set. The spatial and positional accuracy of this information will vary depending on the original source data and methods utilized. For additional details on FWS boundary data refer to http://www.fws.gov/GIS/data/CadastralDB/index.htm. The NLCD layer was produced through a cooperative project conducted by the Multi-Resolution Land Characteristics (MRLC) Consortium. It was developed for the United States at medium spatial resolution. This landcover map and all documents pertaining to it are considered "provisional" until a formal accuracy assessment can be conducted. For a detailed definition and discussion on MRLC and the NLCD 2001 products, refer to Homer et al. (2004) and http://www.mrlc.gov/mrlc2k.asp.

The USGS Land Cover program has combined the tried-and-true methodologies from premier land cover projects, National Land Cover Database (NLCD) and Land Change Monitoring, Assessment, and Projection (LCMAP), together with modern innovations in geospatial deep learning technologies to create the next generation of land cover and land change information. The product suite is called, “Annual NLCD Land Cover Products” and includes four annual products that represent land cover and surface change characteristics of the U.S.: 1) Land Cover, 2) Land Cover Change, 3) Land Cover Confidence, and 4) Spectral Change Day of Year. These Land Cover science product algorithms harness the remotely sensed Landsat data record to provide state-of-the-art land surface change information needed by scientists, resource managers, and decision-makers. Annual NLCD uses a modernized, integrated approach to map, monitor, synthesize, and understand the complexities of land use, cover, and condition change. The Land Cover products are available at https://www.mrlc.gov/data. Legend and Description information is maintained at https://www.mrlc.gov/data/legends/national-land-cover-database-class-legend-and-description.

The U.S. Geological Survey (USGS), in association with the Multi-Resolution Land Characteristics (MRLC) Consortium, produces the National Land Cover Database (NLCD) for the United States. The MRLC, a consortium of federal agencies who coordinate and generate consistent and relevant land cover information at the national scale for a wide variety of environmental, land management, and modeling applications, have been providing the scientific community with detailed land cover products for more than 30 years. Over that time, NLCD has been one of the most widely used geospatial datasets in the U.S., serving as a basis for understanding the Nation’s landscapes in thousands of studies and applications, trusted by scientists, land managers, students, city planners, and many more as a definitive source of U.S. land cover. NLCD land cover suite is created through the classification of Landsat imagery and uses partner data from the MRLC Consortium to help refine many of the land cover classes. The classification system used by NLCD is modified from the Anderson Land Cover Classification System. The NLCD Class Legend and Description is maintained at https://www.mrlc.gov/data/legends/national-land-cover-database-class-legend-and-description. The land cover theme includes two separate products. The first is a standard land cover product suite that provides 16 land cover classes for the conterminous United States and Alaska only land cover types and is available at https://www.mrlc.gov/data. The second product suite, NLCD Land Cover Science Products, provides additional discrimination and land cover classes differentiating grass and shrub and regenerating forest regime from grass and shrub and rangeland setting and is available at https://www.mrlc.gov/nlcd-2021-science-research-products. The latest release of NLCD land cover spans the timeframe from 2001 to 2021 in 2 to 3-year intervals. These new products use a streamlined compositing process for assembling and preprocessing Landsat imagery and geospatial ancillary datasets; a temporally, spectrally, and spatially integrated land cover change analysis strategy; a theme-based post-classification protocol for generating land cover and change products; a continuous fields biophysical parameters modeling method; and a scripted operational system.

The USGS Land Cover program has combined the tried-and-true methodologies from premier land cover projects, National Land Cover Database (NLCD) and Land Change Monitoring, Assessment, and Projection (LCMAP), together with modern innovations in geospatial deep learning technologies to create the next generation of land cover and land change information. The product suite is called, “Annual NLCD Land Cover Products” and includes four annual products that represent land cover and surface change characteristics of the U.S.: 1) Land Cover, 2) Land Cover Change, 3) Land Cover Confidence, and 4) Spectral Change Day of Year. These Land Cover science product algorithms harness the remotely sensed Landsat data record to provide state-of-the-art land surface change information needed by scientists, resource managers, and decision-makers. Annual NLCD uses a modernized, integrated approach to map, monitor, synthesize, and understand the complexities of land use, cover, and condition change. The Land Cover products are available at https://www.mrlc.gov/data. Legend and Description information is maintained at https://www.mrlc.gov/data/legends/national-land-cover-database-class-legend-and-description.

This data set provides a landcover map with 16 landcover classes for the northern coastal plain of the the Arctic National Wildlife Refuge (ANWR) on the North Slope of Alaska. The map was derived from Landsat Thematic Mapper (Landsat TM) data, Digital Elevation Models (DEMs), aerial photographs, existing maps, and extensive ground-truthing. The data used to derive the map cover the period 1982 to 1993.

This update to the Alaska National Land Cover Database (NLCD) 2016 replaces the files dated 20200213. In this update the landcover footprint was extended along the northern coast to include the islands that were missed in previous versions, and several duplicate roads (offset by 1 or 2 pixels) were removed on the Aleutian Islands. The Alaska National Land Cover Database 2016 was created using change detection between the nominal dates of 2011 and 2016 utilizing Google Earth engine composites of Landsat imagery. Traditionally, previous classifications of Alaska used path row data and spectral comparisons between path rows along with ancillary data to derive areas of change. Alaska has many challenges for land cover classification, with the largest of these being a very short “leaf on” imagery season for acceptable phenology. This is compounded by persistent cloud cover during this growing season, and increasing terrain shadow and sun angle problems outside of this season. For this reason, the timeframe of 10 years was needed for the first update to the Alaska land cover in order to have enough acceptable imagery between these 2001 and 2011 nominal dates that met these criteria in order to provide reasonable change detection. For 2016, there was not enough complete path row imagery to do this similar change detection. Google Earth engine was employed to create a composite imagery mosaic that uses much smaller pieces of Landsat imagery to create a complete Landsat imagery snapshot used to create change detection between 2011 and 2016. Although this composite technique is not as scientifically rigorous as utilizing direct Landsat imagery, it was the only method available to us during production that would allow completion of change detection in the desired five year timeframe. The original published 2001 and 2011 Alaska NLCD classifications are generally unchanged, except for slight updates in the northern part of the state to remove perennial ice and snow that were a result of lack of suitable imagery in the 2001 timeframe representing minimum snow and ice extent. See the 2001 and 2011 Land Cover products for the specific metadata process steps associated with the creation of those datasets.

This update to the Alaska National Land Cover Database (NLCD) 2016 replaces the files dated 20200213. In this update the landcover footprint was extended along the northern coast to include the islands that were missed in previous versions, and several duplicate roads (offset by 1 or 2 pixels) were removed on the Aleutian Islands. The Alaska National Land Cover Database 2016 was created using change detection between the nominal dates of 2011 and 2016 utilizing Google Earth engine composites of Landsat imagery. Traditionally, previous classifications of Alaska used path row data and spectral comparisons between path rows along with ancillary data to derive areas of change. Alaska has many challenges for land cover classification, with the largest of these being a very short “leaf on” imagery season for acceptable phenology. This is compounded by persistent cloud cover during this growing season, and increasing terrain shadow and sun angle problems outside of this season. For this reason, the timeframe of 10 years was needed for the first update to the Alaska land cover in order to have enough acceptable imagery between these 2001 and 2011 nominal dates that met these criteria in order to provide reasonable change detection. For 2016, there was not enough complete path row imagery to do this similar change detection. Google Earth engine was employed to create a composite imagery mosaic that uses much smaller pieces of Landsat imagery to create a complete Landsat imagery snapshot used to create change detection between 2011 and 2016. Although this composite technique is not as scientifically rigorous as utilizing direct Landsat imagery, it was the only method available to us during production that would allow completion of change detection in the desired five year timeframe. The original published 2001 and 2011 Alaska NLCD classifications are generally unchanged, except for slight updates in the northern part of the state to remove perennial ice and snow that were a result of lack of suitable imagery in the 2001 timeframe representing minimum snow and ice extent. See the 2001 and 2011 Land Cover products for the specific metadata process steps associated with the creation of those datasets.

This update to the Alaska National Land Cover Database (NLCD) 2016 replaces the files dated 20200213. In this update the landcover footprint was extended along the northern coast to include the islands that were missed in previous versions, and several duplicate roads (offset by 1 or 2 pixels) were removed on the Aleutian Islands. The Alaska National Land Cover Database 2016 was created using change detection between the nominal dates of 2011 and 2016 utilizing Google Earth engine composites of Landsat imagery. Traditionally, previous classifications of Alaska used path row data and spectral comparisons between path rows along with ancillary data to derive areas of change. Alaska has many challenges for land cover classification, with the largest of these being a very short “leaf on” imagery season for acceptable phenology. This is compounded by persistent cloud cover during this growing season, and increasing terrain shadow and sun angle problems outside of this season. For this reason, the timeframe of 10 years was needed for the first update to the Alaska land cover in order to have enough acceptable imagery between these 2001 and 2011 nominal dates that met these criteria in order to provide reasonable change detection. For 2016, there was not enough complete path row imagery to do this similar change detection. Google Earth engine was employed to create a composite imagery mosaic that uses much smaller pieces of Landsat imagery to create a complete Landsat imagery snapshot used to create change detection between 2011 and 2016. Although this composite technique is not as scientifically rigorous as utilizing direct Landsat imagery, it was the only method available to us during production that would allow completion of change detection in the desired five year timeframe. The original published 2001 and 2011 Alaska NLCD classifications are generally unchanged, except for slight updates in the northern part of the state to remove perennial ice and snow that were a result of lack of suitable imagery in the 2001 timeframe representing minimum snow and ice extent. See the 2001 and 2011 Land Cover products for the specific metadata process steps associated with the creation of those datasets.

This update to the Alaska National Land Cover Database (NLCD) 2016 replaces the files dated 20200213. In this update the landcover footprint was extended along the northern coast to include the islands that were missed in previous versions, and several duplicate roads (offset by 1 or 2 pixels) were removed on the Aleutian Islands. The Alaska National Land Cover Database 2016 was created using change detection between the nominal dates of 2011 and 2016 utilizing Google Earth engine composites of Landsat imagery. Traditionally, previous classifications of Alaska used path row data and spectral comparisons between path rows along with ancillary data to derive areas of change. Alaska has many challenges for land cover classification, with the largest of these being a very short “leaf on” imagery season for acceptable phenology. This is compounded by persistent cloud cover during this growing season, and increasing terrain shadow and sun angle problems outside of this season. For this reason, the timeframe of 10 years was needed for the first update to the Alaska land cover in order to have enough acceptable imagery between these 2001 and 2011 nominal dates that met these criteria in order to provide reasonable change detection. For 2016, there was not enough complete path row imagery to do this similar change detection. Google Earth engine was employed to create a composite imagery mosaic that uses much smaller pieces of Landsat imagery to create a complete Landsat imagery snapshot used to create change detection between 2011 and 2016. Although this composite technique is not as scientifically rigorous as utilizing direct Landsat imagery, it was the only method available to us during production that would allow completion of change detection in the desired five year timeframe. The original published 2001 and 2011 Alaska NLCD classifications are generally unchanged, except for slight updates in the northern part of the state to remove perennial ice and snow that were a result of lack of suitable imagery in the 2001 timeframe representing minimum snow and ice extent. See the 2001 and 2011 Land Cover products for the specific metadata process steps associated with the creation of those datasets.

This update to the Alaska National Land Cover Database (NLCD) 2016 replaces the files dated 20200213. In this update the landcover footprint was extended along the northern coast to include the islands that were missed in previous versions, and several duplicate roads (offset by 1 or 2 pixels) were removed on the Aleutian Islands. The Alaska National Land Cover Database 2016 was created using change detection between the nominal dates of 2011 and 2016 utilizing Google Earth engine composites of Landsat imagery. Traditionally, previous classifications of Alaska used path row data and spectral comparisons between path rows along with ancillary data to derive areas of change. Alaska has many challenges for land cover classification, with the largest of these being a very short “leaf on” imagery season for acceptable phenology. This is compounded by persistent cloud cover during this growing season, and increasing terrain shadow and sun angle problems outside of this season. For this reason, the timeframe of 10 years was needed for the first update to the Alaska land cover in order to have enough acceptable imagery between these 2001 and 2011 nominal dates that met these criteria in order to provide reasonable change detection. For 2016, there was not enough complete path row imagery to do this similar change detection. Google Earth engine was employed to create a composite imagery mosaic that uses much smaller pieces of Landsat imagery to create a complete Landsat imagery snapshot used to create change detection between 2011 and 2016. Although this composite technique is not as scientifically rigorous as utilizing direct Landsat imagery, it was the only method available to us during production that would allow completion of change detection in the desired five year timeframe. The original published 2001 and 2011 Alaska NLCD classifications are generally unchanged, except for slight updates in the northern part of the state to remove perennial ice and snow that were a result of lack of suitable imagery in the 2001 timeframe representing minimum snow and ice extent. See the 2001 and 2011 Land Cover products for the specific metadata process steps associated with the creation of those datasets.